Visualizing a Decade of Change in the Arctic Sea Ice Cover

Satellite remote sensing provides the only means to obtain continuous, basin-scale observations of the Arctic Ocean due to its harsh and inaccessible environment. Indeed, satellite data have revolutionized our ability to monitor both seasonal and interannual change on decadal scales. Understanding how the sea ice cover varies in space and time is required to characterize the physical processes governing change, improve sea ice forecasts, and advance longer-term predictions about the future Arctic. An emerging need is access to near-real-time and short-time-critical remote sensing sea ice data products that can be used to support safe maritime activities in ice-infested waters, and for assimilation into sea ice forecasting systems.

Here, we explore novel sea ice data products, derived from spaceborne radar observations acquired during the past ten years. These observations contribute to US Arctic Observing Network (US AON) activities, and in particular are expected to advance collaborative US AON sea ice forecasting activities. We exploit Advanced Scatterometer (ASCAT) radar data for daily tracking of Arctic multi-year sea ice extent, and sea ice dynamics. We describe the techniques used to determine the prevalence of multi-year ice, as well as our validation approach. We place the ASCAT observations in the context of changes in ice thickness, derived from Synthetic Aperture Interferometric Radar Altimeter (SIRAL) observations acquired by CryoSat-2. Interactive touch-screen displays during this eLightning session will provide us the opportunity to share multi-dimensional visualizations illustrating the seasonal evolution of the sea ice cover. We also present high-resolution, decadal-scale videos that reveal interannual variability in sea ice dynamics and drift, multi-year ice extent, and ice thickness. Our sea ice data products are produced routinely, and are publicly-available at the NOAA Laboratory for Satellite Altimetry, and through the NOAA PolarWatch web portal. We demonstrate tools for routine data visualization and data access.